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FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in
  RKHSs

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs

22 March 2024
Sepehr Dehdashtian
Lan Wang
Vishnu Naresh Boddeti
    VLM
ArXivPDFHTML

Papers citing "FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs"

11 / 11 papers shown
Title
Know "No'' Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP
Know "No'' Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP
J. Park
Jungbeom Lee
Jongyoon Song
Sangwon Yu
Dahuin Jung
Sungroh Yoon
45
0
0
19 Jan 2025
DoubleCCA: Improving Foundation Model Group Robustness with Random
  Sentence Embeddings
DoubleCCA: Improving Foundation Model Group Robustness with Random Sentence Embeddings
Hong Liu
Yitong Lu
73
0
0
25 Nov 2024
Joint Vision-Language Social Bias Removal for CLIP
Joint Vision-Language Social Bias Removal for CLIP
Haoyu Zhang
Yangyang Guo
Mohan S. Kankanhalli
VLM
62
0
0
19 Nov 2024
Debiasing Vison-Language Models with Text-Only Training
Debiasing Vison-Language Models with Text-Only Training
Yunfan Yang
Chaoquan Jiang
Zhiyu Lin
Jinlin Xiao
Jiaming Zhang
Jitao Sang
VLM
23
1
0
12 Oct 2024
A Unified Debiasing Approach for Vision-Language Models across
  Modalities and Tasks
A Unified Debiasing Approach for Vision-Language Models across Modalities and Tasks
Hoin Jung
T. Jang
Xiaoqian Wang
VLM
23
2
0
10 Oct 2024
Fairness and Bias Mitigation in Computer Vision: A Survey
Fairness and Bias Mitigation in Computer Vision: A Survey
Sepehr Dehdashtian
Ruozhen He
Yi Li
Guha Balakrishnan
Nuno Vasconcelos
Vicente Ordonez
Vishnu Naresh Boddeti
29
4
0
05 Aug 2024
ED-SAM: An Efficient Diffusion Sampling Approach to Domain
  Generalization in Vision-Language Foundation Models
ED-SAM: An Efficient Diffusion Sampling Approach to Domain Generalization in Vision-Language Foundation Models
Thanh-Dat Truong
Xin Li
Bhiksha Raj
Jackson Cothren
Khoa Luu
DiffM
VLM
33
1
0
03 Jun 2024
Utility-Fairness Trade-Offs and How to Find Them
Utility-Fairness Trade-Offs and How to Find Them
Sepehr Dehdashtian
Bashir Sadeghi
Vishnu Naresh Boddeti
33
6
0
15 Apr 2024
Learning Fair Classifiers with Partially Annotated Group Labels
Learning Fair Classifiers with Partially Annotated Group Labels
Sangwon Jung
Sanghyuk Chun
Taesup Moon
60
45
0
29 Nov 2021
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias
  in Image Search
Are Gender-Neutral Queries Really Gender-Neutral? Mitigating Gender Bias in Image Search
Jialu Wang
Yang Liu
X. Wang
FaML
155
95
0
12 Sep 2021
Fair prediction with disparate impact: A study of bias in recidivism
  prediction instruments
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova
FaML
185
2,079
0
24 Oct 2016
1